https://github.com/python/cpython/commit/b16886528ee43ad8618e81b833be022710c4a8d2
commit: b16886528ee43ad8618e81b833be022710c4a8d2
branch: main
author: Raymond Hettinger <[email protected]>
committer: rhettinger <[email protected]>
date: 2026-04-22T11:52:41-05:00
summary:
Additional itertool recipes for running statistics (gh-148879)
files:
M Doc/library/itertools.rst
diff --git a/Doc/library/itertools.rst b/Doc/library/itertools.rst
index 5a0ac60ab7d2ec..06f8bf2a8b6fa8 100644
--- a/Doc/library/itertools.rst
+++ b/Doc/library/itertools.rst
@@ -833,6 +833,7 @@ and :term:`generators <generator>` which incur interpreter
overhead.
from collections import Counter, deque
from contextlib import suppress
from functools import reduce
+ from heapq import heappush, heappushpop, heappush_max, heappushpop_max
from math import comb, isqrt, prod, sumprod
from operator import getitem, is_not, itemgetter, mul, neg, truediv
@@ -848,11 +849,6 @@ and :term:`generators <generator>` which incur interpreter
overhead.
# prepend(1, [2, 3, 4]) → 1 2 3 4
return chain([value], iterable)
- def running_mean(iterable):
- "Yield the average of all values seen so far."
- # running_mean([8.5, 9.5, 7.5, 6.5]) → 8.5 9.0 8.5 8.0
- return map(truediv, accumulate(iterable), count(1))
-
def repeatfunc(function, times=None, *args):
"Repeat calls to a function with specified arguments."
if times is None:
@@ -1150,6 +1146,49 @@ and :term:`generators <generator>` which incur
interpreter overhead.
return n
+ # ==== Running statistics ====
+
+ def running_mean(iterable):
+ "Average of values seen so far."
+ # running_mean([37, 33, 38, 28]) → 37 35 36 34
+ return map(truediv, accumulate(iterable), count(1))
+
+ def running_min(iterable):
+ "Smallest of values seen so far."
+ # running_min([37, 33, 38, 28]) → 37 33 33 28
+ return accumulate(iterable, func=min)
+
+ def running_max(iterable):
+ "Largest of values seen so far."
+ # running_max([37, 33, 38, 28]) → 37 37 38 38
+ return accumulate(iterable, func=max)
+
+ def running_median(iterable):
+ "Median of values seen so far."
+ # running_median([37, 33, 38, 28]) → 37 35 37 35
+ read = iter(iterable).__next__
+ lo = [] # max-heap
+ hi = [] # min-heap the same size as or one smaller than lo
+ with suppress(StopIteration):
+ while True:
+ heappush_max(lo, heappushpop(hi, read()))
+ yield lo[0]
+ heappush(hi, heappushpop_max(lo, read()))
+ yield (lo[0] + hi[0]) / 2
+
+ def running_statistics(iterable):
+ "Aggregate statistics for values seen so far."
+ # Generate tuples: (size, minimum, median, maximum, mean)
+ t0, t1, t2, t3 = tee(iterable, 4)
+ return zip(
+ count(1),
+ running_min(t0),
+ running_median(t1),
+ running_max(t2),
+ running_mean(t3),
+ )
+
+
.. doctest::
:hide:
@@ -1226,10 +1265,6 @@ and :term:`generators <generator>` which incur
interpreter overhead.
[(0, 'a'), (1, 'b'), (2, 'c')]
- >>> list(running_mean([8.5, 9.5, 7.5, 6.5]))
- [8.5, 9.0, 8.5, 8.0]
-
-
>>> for _ in loops(5):
... print('hi')
...
@@ -1789,6 +1824,28 @@ and :term:`generators <generator>` which incur
interpreter overhead.
True
+ >>> list(running_mean([8.5, 9.5, 7.5, 6.5]))
+ [8.5, 9.0, 8.5, 8.0]
+ >>> list(running_mean([37, 33, 38, 28]))
+ [37.0, 35.0, 36.0, 34.0]
+
+
+ >>> list(running_min([37, 33, 38, 28]))
+ [37, 33, 33, 28]
+
+
+ >>> list(running_max([37, 33, 38, 28]))
+ [37, 37, 38, 38]
+
+
+ >>> list(running_median([37, 33, 38, 28]))
+ [37, 35.0, 37, 35.0]
+
+
+ >>> list(running_statistics([37, 33, 38, 28]))
+ [(1, 37, 37, 37, 37.0), (2, 33, 35.0, 37, 35.0), (3, 33, 37, 38, 36.0),
(4, 28, 35.0, 38, 34.0)]
+
+
.. testcode::
:hide:
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